Immunohistochemical differentiation between primary adenocarcinomas of the ovary and ovarian metastases of colonic and breast origin. Comparison between a statistical and an intuitive approach.

Abstract

AIM: To discriminate between adenocarcinomas that are primary to the ovary and metastatic to the ovary, especially of colonic and breast origin, by immunohistochemistry, using stepwise discriminant analysis or a decision tree. METHODS: 312 routinely processed, formalin fixed tissue specimens were used. The tumours were divided into a learning set (n = 159), composed of primary tumours of ovary, breast, and colon, and a test set, comprising 134 metastases from these sites and an additional 19 primary ovarian carcinomas. The immunohistochemical panel was composed of antibodies against cytokeratin 7 (CK7) and 20 (CK20), CA125, vimentin, carcinoembryonic antigen (CEA), gross cystic disease fluid protein-15 (GCDFP-15), and the oestrogen receptor (ER). The staining results of the tumours were expressed as the product of the staining intensity and the percentage of positive tumour cells. Analyses were first performed on the learning set and then evaluated on the test set. RESULTS: Although the immunostaining patterns showed a considerable overlap between the three types of adenocarcinoma, the breast carcinomas were typically positive for GCDFP-15 and often for ER, and negative for vimentin. Ovarian carcinomas were always positive for CK7 and to a lesser extent for CA125. Colonic carcinomas showed prominent positivity for CEA and CK20, while no staining was seen for ER and vimentin. In discriminant analysis, six antibodies (alpha CK7, alpha CK20, alpha CA125, alpha CEA, alpha ER, and alpha GCDFP-15) appeared to be necessary for optimal classification: 89% of the learning set and 82% of the test set were classified correctly. In the decision tree, only four antibodies (alpha CK7, alpha CEA, alpha ER, and alpha GCDFP-15) were used to obtain a correct classification score of 89% for the learning set and 84% for the test set. CONCLUSIONS: Using a semiquantitative assessment of the immunostaining results by a restricted panel of six antibodies with stepwise discriminant analysis, 80-90% of the adenocarcinomas of colon, breast, and ovary can be correctly classified. Discriminant analysis is computer aided and therefore an easy method and for each case a probability value of the classification result is obtained. The intuitive decision tree method provides a slightly better result, requires only four antibodies, and offers a more practical method for the surgical pathologist.